Automated Test Case Prioritization and Evaluation using Genetic Algorithm
Author
Abstract

Measurement and Metrics Testing - Software testing is one of the most critical and essential processes in the software development life cycle. It is the most significant aspect that affects product quality. Quality and service are critical success factors, particularly in the software business development market. As a result, enterprises must execute software testing and invest resources in it to ensure that their generated software products meet the needs and expectations of end-users. Test prioritization and evaluation are the key factors in determining the success of software testing. Test suit coverage metrics are commonly used to evaluate the testing process. Soft Computing techniques like Genetic Algorithms and Particle Swarm Optimization have gained prominence in various aspects of testing. This paper proposes an automated Genetic Algorithm approach to prioritizing the test cases and the evaluation through code coverage metrics with the Coverlet tool. Coverlet is a.NET code coverage tool that works across platforms and supports line, branch, and method coverage. Coverlet gathers data from Cobertura coverage test runs, which are then utilized to generate reports. Resultant test suits generated were validated and analyzed and have had significant improvement over the generations.

Year of Publication
2022
Date Published
jun
Publisher
IEEE
Conference Location
Kochi, India
ISBN Number
978-1-66546-883-1
URL
https://ieeexplore.ieee.org/document/9885535/
DOI
10.1109/IC3SIS54991.2022.9885535
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